Machine Learning Engineer, Monetization Engineering
Develops and evolves machine learning technology stack for Pinterest's Ads monetization, building personalized recommendation systems using deep learning and LLMs. Requires 2+ years ML experience, CS degree, and expertise in large-scale systems.
About the job
What you’ll do:
- Build cutting edge technology using the latest advances in deep learning and machine learning to personalize Pinterest
- Partner closely with teams across Pinterest to experiment and improve ML models for various product surfaces (Homefeed, Ads, Growth, Shopping, and Search), while gaining knowledge of how ML works in different areas
- Use data driven methods and leverage the unique properties of our data to improve candidates retrieval
- Work in a high-impact environment with quick experimentation and product launches
- Keep up with industry trends in recommendation systems
- Leverage LLMs to enhance content understanding
What we’re looking for:
- 2+ years of industry experience applying machine learning methods (e.g., user modeling, personalization, recommender systems, search, ranking, natural language processing, reinforcement learning, and graph representation learning)
- Degree in computer science, machine learning, statistics, or related field
- End-to-end hands-on experience with building data processing pipelines, large scale machine learning systems, and big data technologies (e.g., Hadoop/Spark)
- Practical knowledge of large scale recommender systems, or modern ads ranking, retrieval, targeting, marketplace systems
Nice to have:
- Publications at top ML conferences
- Expertise in scalable realtime systems that process stream data
- Passion for applied ML and the Pinterest product
- Background in computational advertising
Skills
Machine Learning, Deep Learning, Recommender Systems, Spark, Hadoop, Natural Language Processing, Reinforcement Learning, Graph Representation Learning, LLMs, Computational Advertising
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